Drug Overdose Deaths in the US State Level

#read loan csv file
addiction_data <- read.csv("data/cleaned_addiction.csv")
#addiction_tibble <- tibble(addiction_data) #use tibble to make addiction_data a dataframe

#remove NA rows in the Count_drug_overdose_deaths field 
addiction_dropna <- na.omit(addiction_data)

#load full dataset
full_data <- read_csv("data/joined_data.csv")

#load population data 
pop_data <- read_csv("data/population.csv")

#load the usa map shape file
usa_sf <- read_sf("data/tl_2024_us_state/tl_2024_us_state.shp")

#subset population data to merge with addiction_deathdate_df2 dataframe 
pop_subset <- pop_data %>%
    select(c("fips_code", "state", "area_name", "census_2020_pop"))

#remove row with fips_code = 0 
pop_subset <- pop_subset[pop_subset$state != "US", ]

#rename fips_code column name 
pop_subset <- pop_subset %>%
    rename("FIPS" = "fips_code")

#merge the full_data2 and addiction_deathdate_df2 dataframes 
addiction_pop_join <-  addiction_dropna %>%
    left_join(pop_subset, by = "FIPS")

#create column of overdose deaths total per state
addiction_pop_join2 <- addiction_pop_join %>%
    group_by(STATE_NAME) %>%
    mutate(State_deaths_total = sum(Count_drug_overdose_deaths, na.rm = TRUE))

#create column of overdose deaths per capita state level 
addiction_pop_join2 <- addiction_pop_join2 %>%
    mutate(State_deaths_per_capita = (State_deaths_total/census_2020_pop))

#create column of log transformed overdose deaths per capita at state level 
addiction_pop_join2 <- addiction_pop_join2 %>%
    mutate(Log_state_deaths_per_capita = ifelse(State_deaths_total > 0, log(State_deaths_total), NA))

#create column for text tooltip 
addiction_pop_join2 <- addiction_pop_join2 %>%
    mutate(log_state_hover_text = paste0( 
    "State: ", STATE_NAME, "<br>",
    "State FIP: ", STATEFIPS, "<br>",
    "Average Deaths per Capita: ", State_deaths_total))

#create column for total overdose deaths by county
addiction_pop_join2 <- addiction_pop_join2 %>%
    group_by(COUNTYNAME) %>%
    mutate(Total_overdosedeaths_county = sum(Count_drug_overdose_deaths, na.rm = TRUE))


#create column of overdose deaths per capita count level 
addiction_pop_join2 <- addiction_pop_join2 %>%
    mutate(County_deaths_per_capita = (Total_overdosedeaths_county/census_2020_pop))


#create column of log transformed overdose deaths per capita at county level 
addiction_pop_join2 <- addiction_pop_join2 %>%
    mutate(Log_county_deaths_per_capita = ifelse(County_deaths_per_capita > 0, log(County_deaths_per_capita), NA))

#rename state_name column to name in addiction_pop_join2 
addiction_pop_join2 <- addiction_pop_join2 %>%
    rename("NAME" = "STATE_NAME")

#join addiction_pop_join2 woth usa_sf dataset 
add_pop_sf_join <- usa_sf %>%
    left_join(addiction_pop_join2, by="NAME")

#create choropleth map with log transformed overdose deaths per capita state level
#source code site: https://plotly.com/r/choropleth-maps/

g2 <- list( 
    scope = 'usa',
   projection = list(type = 'albers usa'),
    showlakes = TRUE,
    lakecolor = toRGB('white')
)

fig2 <- plot_ly(
        type="choropleth",
        locations=addiction_pop_join2$ST_ABBREV,
        z=addiction_pop_join2$Log_state_deaths_per_capita,
        text=addiction_pop_join2$log_state_hover_text,
        hoverinfo = "text",
        locationmode = "USA-states",
        colorscale="Viridis",
        colorbar = list(title = "Log Drug Overdose Deaths"),
        marker = list(line = list(width = 0)))

fig2 <- fig2 %>% layout(
    title = "Log Transformed Drug Overdose Deaths \n Per Capita in the US from 2020 to 2024 \n State Level",
    geo = g2)
  
fig2